[1]} predicted hydrogen uptake in mof by predicting 50000+ compounds via a lasso approach with 1000 training gcmc simulations and 12 binned energy features. The energy features were obtained by overlaying a 3D grid on the gcmc simulation box, probing each grid point with a "hydrogen probe" and binning the 3D distribution into a 1D histogram with 12 bins (1 feature per bin). The predictions were screened by retrieving and running gcmc simulations on the top 1000 predictions. The max gcmc simulation in the training data was \(\sim \) 47.5 H2 uptake, and 51 of the top 1000 simulations were \(>\) 45. They synthesized one promising MOF, MFU-4l(Zn), with a predicted \(\sim \) 54 H2 uptake (100 \(\rightarrow \)  5) and experimentally characterized as having 47 H2 uptake (100 \(\rightarrow \)  5) which is competitive with similar experimental mof in the literature.
